In general, this book is full of repetitions, and so it can easily get boring to read. The book shud have been 50-100 pages shorter, then it wud have been much better.

Aside from that, the book is okay. I wudnt particularly recommend reading it, but i wudnt particularly recommend not reading it either. Altho in general one shud not read mediocre books without reason. Time is limited, so one shud read the highest quality material one can find.

Fooled by Randomness – Role of Chance in Markets and Life PROPER

Pre-chapter 1 – SOLON’S WARNING

Part I is concerned with the degree to which a situation may yet, in

the course of time, suffer change. For we can be tricked by situations

involving mostly the activities of the Goddess Fortuna – Jupiter’s

firstborn daughter. Solon was wise enough to get the following point;

that which came with the help of luck could be taken away by luck (and

often rapidly and unexpectedly at that). The flipside, which deserves to

be considered as well (in fact it is even more of our concern), is that

things that come with little help from luck are more resistant to

randomness. Solon also had the intuition of a problem that has obsessed

science for the past three centuries. It is called the problem of induction.

I call it in this book the black swan or the rare event. Solon even

understood another linked problem, which I call the skewness issue; it

does not matter how frequently something succeeds if failure is too

costly to bear.

Wat. Problem of induction is not the same as the black swan fenomenon. Altho they are somewhat related.

Chapter 1 – IF YOU’RE SO RICH WHY AREN’T YOU SO SMART?

Nero holds an undergraduate degree in ancient literature and

mathematics from Cambridge University. He enrolled in a Ph.D.

program in statistics at the University of Chicago but, after completing

the prerequisite coursework, as well as the bulk of his doctoral research,

he switched to the philosophy department. He called the switch “a

moment of temporary sanity”, adding to the consternation of his thesis

director who warned him against philosophers and predicted his return

back to the fold. He finished writing his thesis in philosophy. But not the

Derrida continental style of incomprehensible philosophy (that is,

incomprehensible to anyone outside of their ranks, like myself). It was

quite the opposite; his thesis was on the methodology of statistical

inference in its application to the social sciences. In fact, his thesis was

indistinguishable from a thesis in mathematical statistics – it was just a

bit more thoughtful (and twice as long).

 

I like where this is going. Except that im inclined to think it is incomprehensible to them as well, they are just deluded into thinking that it isnt.

 

Chapter 2 – A BIZARRE ACCOUNTING METHOD

The failure rate of these scientists, though, was better, but only

slightly so than that of MBAs; but it came from another reason, linked

to their being on average (but only on average) devoid of the smallest bit

of practical intelligence. Some successful scientists had the judgment

(and social graces) of a door knob – but by no means all of them. Many

people were capable of the most complex calculations with utmost rigor

when it came to equations, but were totally incapable of solving a

problem with the smallest connection to reality; it was as if they

understood the letter but not the spirit of the math. I am convinced that

X, a likeable Russian man of my acquaintance, has two brains: one for

math and another, considerably inferior one, for everything else (which

included solving problems related to the mathematics of finance). But on

occasion a fast-thinking scientific-minded person with street smarts

would emerge. Whatever the benefits of such population shift, it

improved our chess skills and provided us with quality conversation

during lunchtime – it extended the lunch hour considerably. Consider

that I had in the 1980s to chat with colleagues who had an MBA or tax

accounting background and were capable of the heroic feat of discussing

FASB standards. I have to say that their interests were not too

contagious. The interesting thing about these physicists does not lie in

their ability to discuss fluid dynamics; it is that they were naturally

interested in a variety of intellectual subjects and provide pleasant

conversation.

 

I cud not agree more about fysisists! Thats one reason why i like them. Generally clever and curious people, even if they read far too less to match up with me, and lack rigour in filosofical discussions. Mostly due to no training at all (no logic, no critical thinking etc.).

Chapter 3 – A MATHEMATICAL MEDITATION ON HISTORY

Another analogy would be with grammar; mathematics is often

tedious and insightless grammar. There are those who are interested in

grammar for grammar’s sake, and those interested in avoiding solecisms

while writing documents. We are called “quants” – like physicists, we

have more interest in the employment of the mathematical tool than in

the tool itself. Mathematicians are born, never made. Physicists and

quants too. I do not care about the “elegance” and “quality” of the

mathematics I use so long as I can get the point right. I have recourse to

Monte Carlo machines whenever I can. They can get the work done.

They are also far more pedagogical, and I will use them in this book for

the examples.

I agree 100% with this view of math. A tool, somewhat interesting in itself, but MUCH MORE interesting when it is applicable to something that interests me.

Chapter 4 – RANDOMNESS, NONSENSE, AND THE SCIENTIFIC INTELLECTUAL

One conceivable way to discriminate between a scientific intellectual

and a literary intellectual is by considering that a scientific intellectual can

: usually recognize the writing of another but that the literary intellectual

would not be able to tell the difference between lines jotted down by a

scientist and those by a glib non-scientist. This is even more apparent

when the literary intellectual starts using scientific buzzwords, like

“uncertainty principle”, “Godel’s theorem”, “parallel universe”, or

“relativity” either out of context or, as often, in exact opposition to the

scientific meaning. I suggest reading the hilarious Fashionable Nonsense

by Alan Sokal for an illustration of such practice (I was laughing so loudly

and so frequently while reading it on a plane that other passengers kept

whispering things about me). By dumping the kitchen sink of scientific

references in a paper, one can make another literary intellectual believe

that one’s material has the stamp of science. Clearly, to a scientist, science

lies in the rigor of the inference, not in random references to such

grandiose concepts as general relativity or quantum indeterminacy. Such

rigor can be spelled out in plain English. Science is method and rigor; it

can be identified in the simplest of prose writing. For instance, what

struck me while reading Richard Dawkins’ Selfish Gene3 is that, although

the text does not exhibit a single equation, it seems as if it were translated

from the language of mathematics. Yet it is artistic prose.

I like this! I really want to read Fashionable Nonsense aka. Intellectual Impostures, (review here). But i cant find a fucking ebook version. It is SO annoying to read paper books. They are not easy to quote and discuss!

And paper books are ridiculessly overpriced. Especially textbooks.

Randomness can be of considerable help with the matter. For there is

another, far more entertaining way to make the distinction between the

babbler and the thinker. You can sometimes replicate something that can

be mistaken for a literary discourse with a Monte Carlo generator but it

is not possible randomly to construct a scientific one. Rhetoric can be

constructed randomly, but not genuine scientific knowledge. This is the

application of Turing’s test of artificial intelligence, except in reverse.

What is the Turing test? The brilliant British mathematician, eccentric,

and computer pioneer Alan Turing came up with the following test: a

computer can be said to be intelligent if it can (on average) fool a human

into mistaking it for another human. The converse should be true. A

human can be said to be unintelligent if we can replicate his speech by a

computer, which we know is unintelligent, and fool a human into

believing that it was written by a human. Can one produce a piece of

work that can be largely mistaken for Derrida entirely randomly?

The answer seems to be yes. Aside from the hoax by Alan Sokal (the

same of the hilarious book a few lines ago) who managed to produce

nonsense and get it published by some prominent journal, there are

Monte Carlo generators designed to structure such texts and write entire

papers. Fed with “postmodernist” texts, they can randomize phrases

under a method called recursive grammar, and produce grammatically

sound but entirely meaningless sentences that sound like Jacques

Derrida, Camille Paglia, and such a crowd. Owing to the fuzziness of his

thought, the literary intellectual can be fooled by randomness.

I agree, except that i dont think Paglia is that bad. Altho, she does appear to like The Second Sex according to Wiki, she gave a pretty nice interview along with Summers. I find it difficult to dislike someone who is labeled an “antifeminist” initually. I skimmed her Wikiquote page, and it doesnt appear to have (m)any nonsense quotations like Derrida and others.

Perhaps Taleb has confused her with some other feminist writer? Surely, there are lots of insane ones.

It is hard to resist discussion of artificial history without a comment on

the father of all pseudothinkers, Hegel. Hegel writes a jargon that is

meaningless outside of a chic Left-Bank Parisian cafe or the humanities

department of some university extremely well insulated from the real

world. I suggest this passage from the German “philosopher” (this

passage was detected, translated and reviled by Karl Popper):

Sound is the change in the specific condition of segregation of the

material parts, and in the negation of this condition; merely an

abstract or an ideal ideality, as it were, of that specification. But this

change, accordingly, is itself immediately the negation of the material

specific subsistence; which is, therefore, real ideality of specific

gravity and cohesion, i.e. – heat. The heating up of sounding bodies,

just as of beaten and or rubbed ones, is the appearance of heat,

originating conceptually together with sound.

Even a Monte Carlo engine could not sound as random as the great

philosophical master thinker (it would take plenty of sample runs to get

the mixture of heat and sound). People call that philosophy and

frequently finance it with taxpayer subsidies! Now consider that

Hegelian thinking is generally linked to a “scientific” approach to

history; it has produced such results as Marxist regimes and even a

branch called “neo-Hegelian” thinking. These “thinkers” should be

given an undergraduate-level class on statistical sampling theory prior to

their release in the open world.

Good title. Ill refer to him as that from now on.

Think this is obscure filosofy? It isnt. It is common. There are multiple mandatory exams where one can pick Hegel in the Aarhus University Department of Philosophy.

Yes, they dun goofed.

There are instances where I like to be fooled by randomness. My allergy

to nonsense and verbiage dissipates when it comes to art and poetry. On

the one hand, I try to define myself and behave officially as a no-

nonsense hyper-realist ferreting out the role of chance; on the other,

have no qualms indulging in all manner of personal superstitions. Where

do I draw the line? The answer is aesthetics. Some aesthetic forms

appeal to something genetic in us, whether or not they originate in

random associations or plain hallucination. Something in our human

genes is deeply moved by the fuzziness and ambiguity of language; then

why fight it?

The poetry and language-lover in me was initially depressed by the

account of the Exquisite Cadavers poetic exercise where interesting and

poetic sentences are randomly constructed. By throwing enough words

together, some unusual and magical-sounding metaphor is bound to

emerge according to the laws of combinatorics. Yet one cannot deny

that some of these poems are of ravishing beauty. Who cares about their

origin if they manage to please our aesthetic senses?

Answer: people who commit the genetic fallacy.

Chapter 6 – SKEWNESS AND ASYMMETRY

When I was in the employment of the New York office of a large

investment house, I was subjected on occasions to the harrying weekly

“discussion meeting”, which gathered most professionals of the New York

trading room. I do not conceal that I was not fond of such gatherings, and

not only because they cut into my gym time. While the meetings included

traders, that is, people who are judged on their numerical performance, it

was mostly a forum for salespeople (people capable of charming

customers), and the category of entertainers called Wall Street

“economists” or “strategists” who make pronouncements on the fate of

the markets, but do not engage in any form of risk taking, thus having their

success dependent on rhetoric rather than actually testable facts. During

the discussion, people were supposed to present their opinions on the state

of the world. To me, the meeting was pure intellectual pollution. Everyone

had a story, a theory, and insights that they wanted others to share. I resent

the person who, without having done much homework in libraries, thinks

that he is onto something rather original and insightful on a given subject

matter (and respect people with scientific minds like my friend Stan Jonas

who feel compelled to spend their nights reading wholesale on a subject

matter, trying to figure out what was done on the subject by others before

emitting an opinion – would the reader listen to the opinion of a doctor

who does not read medical papers?).

I have to confess that my optimal strategy (to soothe my boredom

and allergy to confident platitudes) was to speak as much as I could,

while totally avoiding listening to other people’s replies by trying to

solve equations in my head. Speaking too much would help me clarify

my mind, and, with a little bit of luck, I would not be “invited” back

(that is, forced to attend) the following week.

Hahaha. What is not to like about this guy? :D He is ofc right about speaking wanting to speak about stuff they know nothing about. There are a few subjects where this ALWAYS happens: IQ-research, politics, filosofy of religion. I think the most annoying is the first, since the science on the matter is so clear. I have definitely changed my mind from initial skepticism towards wholeheartedly embracing it. Most people are still stuck in the “initial skepticism” fase, and they never get out of it becus they dont read. I keep mocking people. They have not even read the mean Wikipedia article about it, but they keep criticizing the research for dumb reasons that have been refuted decades ago, ex. tests are biased (dealing with racial issues), tests dont measure anything useful, one cannot ‘reduce intelligence to one number’ (not even sure what this means, if anything), etc.

I must admit to copying his strategy of talking as much as possible. Altho, keep in mind that “Generally speaking, you aren’t learning much when your lips are moving.”. But then again, i dont generally socialize to learn stuff. Learning stuff is best done at home, reading.

Note that the economist Robert Lucas dealt a blow to econometrics

by arguing that if people were rational then their rationality would

cause them to figure out predictable patterns from the past and adapt, so

that past information would be completely useless for predicting the

future (the argument, phrased in a very mathematical form, earned him

a Nobel Memorial Prize in Economics). We are human and act

according to our knowledge, which integrates past data. I can translate

his point with the following analogy. If rational traders detect a pattern

of stocks rising on Mondays, then, immediately such a pattern becomes

detectable, it would be ironed out by people buying on Friday in

anticipation of such an effect. There is no point searching for patterns

that are available to everyone with a brokerage account; once detected,

they would be ironed out.

I hope he did more than that to get the nobel prize. I have that of that concept many times, altho never mentined it to anyone IIRC. Wud be nice with some 2e+6 swedish kronor.

Somehow, what came to be known as the Lucas critique was not

carried through by the “scientists”. It was confidently believed that the

scientific successes of the industrial revolution could be carried through

into the social sciences, particularly with such movements as Marxism.

Pseudoscience came with a collection of idealistic nerds who tried to

create a tailor-made society, the epitome of which is the central planner.

Economics was the most likely candidate for such use of science; you

can disguise charlatanism under the weight of equations, and nobody

can catch you since there is no such thing as a controlled experiment.

Now the spirit of such methods, called scientism by its detractors (like

myself), continued past Marxism, into the discipline of finance as a few

technicians thought that their mathematical knowledge could lead them

to understand markets. The practice of “financial engineering” came

along with massive doses of pseudoscience. Practitioners of these

methods measure risks, using the tool of past history as an indication of

the future. We will just say at this point that the mere possibility of the

distributions not being stationary makes the entire concept seem like a

costly (perhaps very costly) mistake. This leads us to a more

fundamental question: the problem of induction, to which we will turn

in the next chapter.

Historicism has always bothered me, altho i never studied it in detail. I dont think i have even done the bare minimum of reading the Wikipedia page. Does the Lucasian argument from before show that it is impossible to do historicism. It seems not, altho it goes some of the way. Clearly, there are patterns in history. Perhaps we have just not created some workable general theory(+pl) of history like we have in fysics or biology. Either becus it isnt possible, or becus we havent tried hard enough, or becus we are not clever enough, or becus we have too little data. I dont really know. Altho, if i had to bet, id bet against any such general theory of history.

Chapter 7 – THE PROBLEM OF INDUCTION

Popper came up with a major answer to the problem of induction (to me

he came up with the answer). No man has influenced the way scientists

do science more than Sir Karl – in spite of the fact that many of his

fellow professional philosophers find him quite naive (to his credit, in

my opinion). Popper’s idea is that science is not to be taken as seriously

as it sounds (Popper when meeting Einstein did not take him as the

demigod he thought he was). There are only two types of theories:

1. Theories that are known to be wrong, as they were tested and

adequately rejected (he calls them falsified).

2. Theories that have not yet been known to be wrong, not falsified yet,

but are exposed to be proved wrong.

Why is a theory never right? Because we will never know if all the

swans are white (Popper borrowed the Kantian idea of the flaws in our

mechanisms of perception). The testing mechanism may be faulty.

However, the, statement that there is a black swan is possible to make. A

theory cannot b’e verified. To paraphrase baseball coach Yogi Berra

again, past data has a lot of good in it, but it is the bad side that is bad. It

can only be provisionally accepted. A theory that falls outside of these

two categories is not a theory. A theory that does not present a set of

conditions under which it would be considered wrong would be termed

charlatanism – they would be impossible to reject otherwise. Why?.

Because the astrologist can always find a reason to fit the past event, by

saying that Mars was probably in line but not too much so (likewise to

me a trader who does not have a point that would make him change his

mind is not a trader). Indeed the difference between Newtonian physics,

which was falsified by Einstein’s relativity, and astrology lies in the

following irony. Newtonian physics is scientific because it allowed us to

falsify it, as we know that it is wrong, while astrology is not because it

does not offer conditions under which we could reject it. Astrology

cannot be disproved, owing to the auxiliary hypotheses that come into

play. Such point lies at the basis of the demarcation between science and

nonsense (called “the problem of demarcation”).

I swear one day i will write something about the cliché Popperian writings. Difficult to believe that a phd cud have written this. It is full of the usual dumb stuff like obvious internal inconsistencies in language use like “A theory that falls outside of these two categories is not a theory.” or what about obviously wrong things like the confusion with demarcation principle (dividing things into science and non-science), falsification principle (a proposed demarcation principle) and meaningfulness. He is using falsification as a reverse verificationism of meaning.

Then there are things like “Newtonian physics is scientific because it allowed us to falsify it” giving the reader the idea, that being falsified is a sufficient condition for being science. Eh.

And whats with astrology as nonfalsifiable? There have been lots of studies that falsify various parts of astrology. It is very much falsified, and it is not scientific becus of that.

This part leaves me greatly disappointed.

Chapter 9 – IT IS EASIER TO BUY AND SELL THAN FRY AN EGG

You get an anonymous letter on January 2nd informing you that the

market will go up during the month. It proves to be true, but you

disregard it owing to the well-known January effect (stocks have gone

up historically during January). Then you receive another one on Feb 1st

telling you that the market will go down. Again, it proves to be true.

Then you get another letter on March 1st – same story. By July you are

intrigued by the prescience of the anonymous person and you are asked

to invest in a special offshore fund. You pour all your savings into it.

Two months later, your money is gone. You go spill your tears on your

neighbor’s shoulder and he tells you that he remembers that he received

two such mysterious letters. But the mailings stopped at the second

letter. He recalls that the first one was correct in its prediction, the other

incorrect.

What happened? The trick is as follows. The con operator pulls

10,000 names out of a phone book. He mails a bullish letter to one half

of the sample, and a bearish one to the other half. The following month

he selects the names of the persons to whom he mailed the letter whose

prediction turned out to be right, that is, 5,000 names. The next month

he does the same with the remaining 2,500 names, until the list narrows

down to 500 people. Of these there will be 200 victims. An investment

in a few thousand dollars worth of postage stamps will turn into several

million.

This is a rather clever scam.

The birthday paradox

The most intuitive way to describe the data mining problem to a non-

statistician is through what is called the birthday paradox, though it is

not really a paradox, simply a perceptional oddity. If you meet

someone randomly, there is a one in 365.25 chance of your sharing

their birthday, and a considerably smaller one of having the exact

birthday of the same year. So, sharing the same birthday would be a

coincidental event that you would discuss at the dinner table. Now let

us look at a situation where there are 23 people in a room. What is the

chance of there being two people with the same birthday? About 50%.

For we are not specifying which people need to share a birthday; any

pair works.

I am familiar with the scenario, but is it really that easy to deal with leap year birthdays? It seems not. To make it easy, let’s say that we are looking at a 4-year period. For illustration purposes, let’s talk about marbles with numbers on them in a pool. They have numbers from 1 to 366. For every number except 60 (31 days in january, 29 days in february) there are 4 marbles with that number. There is only one marble with the number 6. In total there are 4·365+1=1461 marbles. With replacement, is the chance of picking a marble, noting the number, blending them, picking a marble again and noting the same number realy 365.25? My intuition says that it is 365+1/8 instead becus of the increased rarity of that marble.

Suppose a person P has birthday on the 1st january. What is his chance of meeting someone with the same birthday? 4 in 1461 = 1 in 365.25. So far so good.

Suppose a person S has birthday on the 29th february. What is his chance of meeting someone with the same birthday? 1 in 1461 ≠ 1 in 365.25.

Im not sure how to add these up to get the average chance. Surely, it very rarely happens that two people born on the 29th february meet each other. This should be reflected in the probability for the average person. It seems to me that his number does not take this into account. It is implicitly ‘assuming’ that the first person is not born on the 29th february.

Im sure a mathematician can solve his and either prove me right or wrong. Another way is just to program a test of it, which might be faster than trying to solve it mathematically.

Chapter 11 – RANDOMNESS AND OUR BRAIN: WE ARE PROBABILITY BLIND

Who are the most influential economists of the century, in terms of

journal references, their followings, and their influence over the

profession? No, it is not John Maynard Keynes, not Alfred Marshall,

not Paul Samuelson, and certainly not Milton Friedman. They are

Daniel Kahneman and Amos Tversky, psychology researchers whose

specialty was to uncover areas where human beings are not endowed

with rational thinking and optimal economic behavior.

The pair taught us a lot about the way we perceive and handle

uncertainty. Their research, conducted on a population of students and

professors in the early 1970s, showed that we do not correctly

understand contingencies. Furthermore, they showed that in the rare

cases when we understand probability, we do not seem to consider it in

our behavior. Since the Kahneman and Tversky results, an entire

discipline called behavioral finance and economics has flourished. It is in

open contradiction with the orthodox so-called neoclassical economics

taught in business schools under the normative names of efficient

markets, rational expectations, and other such concepts. It is worth

stopping, at this juncture, and discussing the distinction between

normative and positive sciences. A normative science (clearly a self-

contradictory concept) offers prescriptive teachings; it studies how

things should be. Some economists, for example, (those of the efficient

market religion) believe that humans are rational and act rationally

because it is the best thing for them to do (it is mathematically

“optimal”). The opposite is a positive science, which is based on how

people actually are observed to behave. In spite of econQmists’ envy of

physicists, physics is an inherently positive science while economics,

particularly microeconomics and financial economics, is predominantly

a normative one.

A normative science is ‘clearly’ a contradiction? That reminds me of the Peircian definition of “logic”, which is similar to the one found here “Briefly speaking, we might define logic as the study of the principles of correct reasoning.”.

The soft sciences of psychology and economics have cheated us on

occasions in the past. How? Economics has produced laughable ideas,

ideas that evaporate once one changes the assumptions a little bit. It

seems difficult to take sides with bickering economists trading often-

incomprehensible arguments (even to economists). Biology and

medicine, on the other hand, rank higher in scientific firmness; like

true sciences, they can explain things while at the same time being

subjected to falsification. They are both positive and their theories are

better theories, that is, more easily testable. The good news is that

neurologists are starting to confirm these results, with what is called

environment mapping in the brain, by taking a patient whose brain is

damaged in one single spot (say, by a tumor or an injury deemed to be

local) and deducing by elimination the function performed by such part

of the aniatomy. This isolates the parts of the brain that perform the

various functions. The Kahneman and Tversky results thus found a terra

firma with the leaps in our knowledge obtained through behavioral

genetics and, farther, plain medicine. Some of the physiology of our

brain makes us perceive things and behave in a given manner. We are,

whether we like it or not, prisoners of our biology.

Researchers in evolutionary psychology provide convincing reasons

for these biases. We have not had the incentive to develop an ability to

understand probability because we did not have to do so – but the more

profound reason is that we are not designed to understand things. We

are built only to survive and procreate. To survive, we need to overstate

some probabilities, such as those that can affect our survival. For

instance, those whose brain imparted higher odds to dangers of death, in

other words the paranoid, survived and gave us their genes (provided

such paranoia did not come at too high a cost, otherwise it would have

been a drawback). Our brain has been wired with biases that may

hamper us in a more complex environment, one that requires a more

accurate assessment of probabilities.

The story of these biases is thus being corroborated by the various

disciplines; the magnitude of the perceptional distortions makes us less

than rational, in the sense of both having coherent beliefs (i.e. free of

logical contradictions) and acting in a manner compatible with these

beliefs.

What he is talking about is called error management theory. See Handbook of Evolutionary Psychology, ex. p. 241.

Chapter 13 – CARNEADES COMES TO ROME: ON PROBABILITY AND SKEPTICISM

I conclude with the following saddening remark about scientists in the

soft sciences. People confuse science and scientists. Science is great, but

individual scientists are dangerous. They are human; they are marred by

the biases humans have. Perhaps even more. For most scientists are hard

headed, otherwise they would not derive the patience and energy to

perform the Herculean tasks asked of them, like spending 18 hours a

day perfecting their doctoral thesis.

A scientist may be forced to act like a cheap defense lawyer rather

than a pure seeker of the truth. A doctoral thesis is “defended” by the

applicant; it would be a rare situation to see the student change his mind

upon being supplied with a convincing argument. But science is better

than scientists. It was said that science evolves from funeral to funeral.

After the LTCM collapse, a new financial economist will emerge, who

will integrate such knowledge in his science. He will be resisted by the

older ones but, again, they will be much closer to their funeral date than

he.

The saying he is referring to (without source) is this one:

“A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it. “ (source)

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